An Enhanced End to End Route Discovery in AODV using Multi-Objectives Genetic Algorithm

This paper presents a multi objectives genetic algorithm approach for the Ad-hoc On-Demand Distance Vector (AODV) Routing Protocol for Wireless Sensor Network (WSN). AODV used individual routing metric in the form of minimum-hop count and this led to generate two problems: First, utilizing shortest path all time that can be overloaded in the selected path which produce to unbalanced energy depletion and traffic congestion. Secondly, routing during short path and weak link quality is more harmful than over long path strong link quality as it can suffer retransmissions and packet drops. The proposed algorithm will overcome these problems by using Genetic algorithm in which composite multi metric routing criterion are used by integrating three parameters energy factor, traffic load and hop factor the protocol called MGAOVD. Routing based multiple criterions can be combined into a individual criterion to get better performance. The MGAOVD proposed protocol implemented using simulation environments using NS2 simulation. Results from MGAOVD proposed algorithm show outperform compare to original AODV in terms of increase packet delivery ratio, decreased energy consumption, decreased end-to-end delay, and decreased overhead.